Single-cell RNA-seq dictionary of in vivo immune responses to cytokines

Cytokines mediate cell-cell communication in the immune system and represent important therapeutic targets. While there have been in-depth studies of individual cytokines, we lack a global view of the responses of each major immune cell type to each cytokine. To address this gap we created the Immune Dictionary — a compendium of single-cell transcriptomic profiles of over 17 immune cell types in response to each of 86 cytokines in murine lymph nodes in vivo. A cytokine-centric view of the dictionary revealed that most cytokines induce highly cell-type-specific responses. For example, the inflammatory cytokine IL-1ß induced distinct gene programs in almost every cell type. A cell-type-centric view identified both known and previously uncharacterized cytokine-induced polarization states in every immune cell type, such as a polyfunctional state of NK cells induced by IL-18. Based on the dictionary, we developed companion software, Immune Response Enrichment Analysis (IREA), for assessing immune cell polarization and cytokine activities in any transcriptomic data, and applied it to infer cytokine networks in tumors following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states in each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell-cell communication networks in any immune response. Overall design: We systematically profiled single-cell transcriptomic responses in vivo to 86 cytokines. The 86 cytokines were selected to represent most of the members in each major cytokine family, including: IL-1 (IL-1a/1ß/Ra/18/33/36a/36Ra), common ? chain (IL-2/4/7/9/15/21), common ß chain (GM-CSF/IL-3/IL-5), IL-6 (IL-6/11/27*/31, LIF, OSM, CT-1, NP), IL-12 (IL-12/23/27*/Y), IL-10 (IL-10/19/20/22/24), IL-17 (IL-17A-F), interferon (IFN-a1/ß/e/?/?/?2), TNF (TNFSF1-15, 13B, 18), complement (C3a, C5a), and a small number of representative cytokines from other protein families with less well-characterized immune functions (e.g.,Persephins, Adiponectin). Carrier-free cytokines were freshly reconstituted and administered into distinct wild-type C57BL6/J mice (3 mice per cytokine as biological replicates). PBS (vehicle) treated samples were included in each batch as controls. Draining lymph nodes were collected 4 hours after treatment and freshly processed using an optimized protocol for viable cell recovery. Data quality, including batch-to-batch consistency, was experimentally strictly controlled for and computationally verified. Single-cell profiling of lymph node cells was performed Chromium Single Cell 3' Library & Gel Bead v3 Kit (10x Genomics) to generate single-cell transcriptomes for 386,703 cells that passed quality control.

细胞因子（cytokine）介导免疫系统中的细胞间通讯，是重要的治疗靶点。尽管已有针对单个细胞因子的深入研究，但我们尚未全面掌握每种主要免疫细胞类型对各类细胞因子的应答情况。为填补这一研究空白，我们构建了免疫字典（Immune Dictionary）：该数据集收录了体内小鼠淋巴结中，17种以上免疫细胞类型分别应答86种细胞因子后的单细胞转录组图谱。

以细胞因子为中心分析该字典发现，大多数细胞因子可诱导具有高度细胞类型特异性的应答。例如，炎性细胞因子IL-1β可在几乎所有细胞类型中诱导独特的基因表达程序。以细胞类型为中心的分析则在每种免疫细胞类型中，识别出了已知的、以及此前未被表征的细胞因子诱导极化状态，例如IL-18诱导NK细胞产生的多功能激活状态。

基于该字典，我们开发了配套软件免疫应答富集分析（Immune Response Enrichment Analysis，IREA），用于在任意转录组数据中评估免疫细胞极化状态与细胞因子活性；我们还将其应用于推断免疫检查点阻断治疗后肿瘤内的细胞因子网络。本字典可为细胞因子功能研究提供全新假说，阐明细胞因子的多效性作用，拓展我们对各类免疫细胞激活状态的认知，并为推断特定细胞因子与细胞间通讯网络在任意免疫应答中的作用提供分析框架。

实验整体设计：
我们系统地表征了体内86种细胞因子诱导的单细胞转录组应答。我们选取的86种细胞因子覆盖了各主要细胞因子家族的绝大多数成员，包括：IL-1家族（IL-1α/1β/IL-1Ra/18/33/36α/36Ra）、共同γ链受体家族（IL-2/4/7/9/15/21）、共同β链受体家族（GM-CSF/IL-3/IL-5）、IL-6家族（IL-6/11/27*/31、LIF、OSM、CT-1、NP）、IL-12家族（IL-12/23/27*/Y）、IL-10家族（IL-10/19/20/22/24）、IL-17家族（IL-17A-F）、干扰素家族（IFN-α1/β/ε/η/κ/ζ2）、TNF家族（TNFSF1-15、13B、18）、补体家族（C3a、C5a），以及少量来自其他蛋白家族、免疫功能尚待深入解析的代表性细胞因子（如Persephins、脂联素（Adiponectin））。

我们使用无载体细胞因子，新鲜复溶后分别注入不同的野生型C57BL/6J小鼠体内（每种细胞因子设置3只小鼠作为生物学重复）。每批实验均设置PBS（溶剂对照）处理的样本作为对照。于细胞因子处理4小时后收集引流淋巴结，并采用优化的活细胞回收方案进行新鲜样本处理。我们通过实验严格控制并通过计算验证了数据质量，包括批间一致性。我们采用Chromium单细胞3'端文库与磁珠v3试剂盒（10x Genomics）对淋巴结细胞开展单细胞转录组分析，最终为386703个通过质量控制的细胞生成了单细胞转录组数据。